RAMA 18 explore

import bay
import xarray as xr
import hvplot.xarray
import numpy as np

wda = xr.load_dataset("/Users/dcherian/work/bay/estimates/rama18-15N-wda.nc")
ra18 = xr.load_dataset("/Users/dcherian/work/bay/estimates/rama18-15N.nc")

def hvplot_χpod(pod, **kwargs):
    kw = dict(width=1100, height=200)
    kwargs.update({"line_width": 1})
    if "KT" in pod:
        pod = pod.rename({"KT": "Kt", "Tz": "dTdz"})

    return (
        pod.chi.hvplot.line(x="time", logy=True, **kwargs).opts(**kw)
        + pod.Kt.hvplot.line(x="time", logy=True, **kwargs).opts(**kw)
        + pod.dTdz.hvplot.line(x="time", **kwargs, logy=False).opts(**kw)
        + pod.Jq.hvplot.line(x="time", **kwargs, logy=False).opts(**kw)
    ).cols(1)

Mooring stratification

Uses dTdz from mooring CTDs 10ish-m apart.

min_dTdz > 1e-3 C/m

These are 10minute averages

hvplot_χpod(ra18, by="depth")

Sorted Internal stratification

Uses dTdz computed from sorted “profiles” recorded as χpod is pumped up and down by surface gravity waves. This are 1 minute averages

hvplot_χpod(wda, by="depth")